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5,099 results on '"XIA, Hui"'

2. Specific convulsions and brain damage in children hospitalized for Omicron BA.5 infection: an observational study using two cohorts

Author

Pei, Yuan-Yuan, Wang, Hong-Li, Yin, Gen-Quan, Xu, Yi, Tan, Jian-Hao, Liang, Xin-Hua, Wu, Hui-Ying, Yin, Xun-Tao, Fang, Chun-Xiao, Peng, Jun-Zheng, Wu, Zhi-Yuan, Sun, Yi, Dang, Run, Liang, Yu-Feng, Tang, Hong-Mei, Li, You-Yi, Qiao, Zhong-Xiang, Liang, Zhi-Cheng, Tang, Jian-Ping, Zeng, Fan-Sen, Zheng, Ke-Lu, Zeng, Yi-Ru, Cao, Xiao-Jun, Xia, Hui-Min, Wei, Jian-Rui, Tang, Jin-Ling, and Gong, Si-Tang

Published
2024
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11. Numerically stable neural network for simulating Kardar-Parisi-Zhang growth in the presence of uncorrelated and correlated noises

Author

Song, Tianshu and Xia, Hui

Subjects
Physics - Computational Physics, Condensed Matter - Statistical Mechanics
Abstract

Numerical simulations are essential tools for exploring the dynamic scaling properties of the nonlinear Kadar-Parisi-Zhang (KPZ) equation. Yet the inherent nonlinearity frequently causes numerical divergence within the strong-coupling regime using conventional simulation methods. To sustain the numerical stability, previous works either utilized discrete growth models belonging to the KPZ universality class or modified the original nonlinear term by the designed specified operators. However, recent studies revealed that these strategies could cause abnormal results. Motivated by the above-mentioned facts, we propose a convolutional neural network-based method to simulate the KPZ equation driven by uncorrelated and correlated noises, aiming to overcome the challenge of numerical divergence, and obtaining reliable scaling exponents. We first train the neural network to represent the determinant terms of the KPZ equation in a data-driven manner. Then, we perform simulations for the KPZ equation with various types of temporally and spatially correlated noises. The experimental results demonstrate that our neural network could effectively estimate the scaling exponents eliminating numerical divergence.

Published
2023

24. Progress in Diets with Low Glycemic Index for the Nutritional Management of Type 2 Diabetes: Research and Current Applications

Author

LI Aiqi, XIA Hui, SUN Guiju

Subjects
low glycemic index foods, glycemic index, type 2 diabetes mellitus, nutritional management, blood glucose management, Food processing and manufacture, TP368-456
Abstract

Foods with a glycemic index (GI) equal to or less than 55 are known as low GI foods. A low GI diet refers to a dietary pattern in which low GI foods are primarily chosen, and cooking methods are adjusted to control the overall GI value of the diet. The application of a low GI dietary intervention in the nutritional management of diabetes helps to stabilize postprandial blood glucose, improve satiety, and reduce blood glucose fluctuations in diabetic patients. This article provides a systematic review of the application of low GI dietary patterns in the nutritional management for diabetes, elucidates the factors influencing dietary GI value, discusses the types and development of low GI foods, presents an outlook for future development trends, and proposes future research directions and potential challenges in the field of low GI foods.

Published
2024
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25. DFDS: Data-Free Dual Substitutes Hard-Label Black-Box Adversarial Attack

Author

Jiang, Shuliang, He, Yusheng, Zhang, Rui, Kang, Zi, Xia, Hui, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Cao, Cungeng, editor, Chen, Huajun, editor, Zhao, Liang, editor, Arshad, Junaid, editor, Asyhari, Taufiq, editor, and Wang, Yonghao, editor

Published
2024
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26. Scalable Attack on Graph Data by Important Nodes

Author

Hu, Wenjiang, Ma, Mingda, Jiang, Yanan, Xia, Hui, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Cao, Cungeng, editor, Chen, Huajun, editor, Zhao, Liang, editor, Arshad, Junaid, editor, Asyhari, Taufiq, editor, and Wang, Yonghao, editor

Published
2024
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27. Invisible Backdoor Attacks on Key Regions Based on Target Neurons in Self-Supervised Learning

Author

Qian, Xiangyun, He, Yusheng, Zhang, Rui, Kang, Zi, Sheng, Yilin, Xia, Hui, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Cao, Cungeng, editor, Chen, Huajun, editor, Zhao, Liang, editor, Arshad, Junaid, editor, Asyhari, Taufiq, editor, and Wang, Yonghao, editor

Published
2024
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28. Collaborative Adversarial Learning for Unsupervised Federated Domain Adaptation

Author

Chi, Hao, Zhang, Yingqi, Xu, Shuo, Zhang, Rui, Xia, Hui, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Cao, Cungeng, editor, Chen, Huajun, editor, Zhao, Liang, editor, Arshad, Junaid, editor, Asyhari, Taufiq, editor, and Wang, Yonghao, editor

Published
2024
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29. Electric Vehicle Charging Load Forecasting Based on Improved Gipps and Its Impact on the Distribution Network

Author

Xia, Hui, Zheng, Shicheng, Lang, Jiahong, Hua, Yuting, Zhang, Qian, Wu, Hongbin, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Yang, Qingxin, editor, Li, Zewen, editor, and Luo, An, editor

Published
2024
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32. Power Analysis and Experimental Study of Vortex-Excited Vibrating Ocean Current Energy Generation Based on a Cylindrical Permanent Magnet Linear Motor

Author

Fan, Liguo, Liu, Guoqiang, Song, Xianjin, Zhang, Wenwei, Wu, Lipeng, Xia, Hui, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Yang, Qingxin, editor, Li, Zewen, editor, and Luo, An, editor

Published
2024
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33. Simulation of Magneto-Acousto-Electrical Tomography Based on Approximately Realistic Numerical Breast Model

Author

Zhang, Wenwei, Liu, Guoqiang, Xia, Hui, Li, Yuanyuan, Li, Shiqiang, Li, Xiaonan, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Cai, Chunwei, editor, Qu, Xiaohui, editor, Mai, Ruikun, editor, Zhang, Pengcheng, editor, Chai, Wenping, editor, and Wu, Shuai, editor

Published
2024
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34. Design and Simulation Analysis of a New Cylindrical Permanent Magnet Linear Motor for Vortex-Induced Vibration Ocean Current Power Generation

Author

Fan, Liguo, Liu, Guoqiang, Song, Xianjin, Zhang, Wenwei, Jin, Tongyang, Wu, Lipeng, Xia, Hui, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Dong, Xuzhu, editor, and Cai, Li, editor

Published
2024
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35. QESAR: Query Effective Decision-Based Attack on Skeletal Action Recognition

Author

Kang, Zi, Zhang, Yumei, Zhang, Rui, Jiang, Yanan, Xia, Hui, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Liu, Qingshan, editor, Wang, Hanzi, editor, Ma, Zhanyu, editor, Zheng, Weishi, editor, Zha, Hongbin, editor, Chen, Xilin, editor, Wang, Liang, editor, and Ji, Rongrong, editor

Published
2024
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40. FRIB: Low-poisoning Rate Invisible Backdoor Attack based on Feature Repair

Author

Xia, Hui, Yang, Xiugui, Qian, Xiangyun, and Zhang, Rui

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

During the generation of invisible backdoor attack poisoned data, the feature space transformation operation tends to cause the loss of some poisoned features and weakens the mapping relationship between source images with triggers and target labels, resulting in the need for a higher poisoning rate to achieve the corresponding backdoor attack success rate. To solve the above problems, we propose the idea of feature repair for the first time and introduce the blind watermark technique to repair the poisoned features lost during the generation of poisoned data. Under the premise of ensuring consistent labeling, we propose a low-poisoning rate invisible backdoor attack based on feature repair, named FRIB. Benefiting from the above design concept, the new method enhances the mapping relationship between the source images with triggers and the target labels, and increases the degree of misleading DNNs, thus achieving a high backdoor attack success rate with a very low poisoning rate. Ultimately, the detailed experimental results show that the goal of achieving a high success rate of backdoor attacks with a very low poisoning rate is achieved on all MNIST, CIFAR10, GTSRB, and ImageNet datasets.

Published
2022

41. AdvSmo: Black-box Adversarial Attack by Smoothing Linear Structure of Texture

Author

Xia, Hui, Zhang, Rui, Jiang, Shuliang, and Kang, Zi

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Black-box attacks usually face two problems: poor transferability and the inability to evade the adversarial defense. To overcome these shortcomings, we create an original approach to generate adversarial examples by smoothing the linear structure of the texture in the benign image, called AdvSmo. We construct the adversarial examples without relying on any internal information to the target model and design the imperceptible-high attack success rate constraint to guide the Gabor filter to select appropriate angles and scales to smooth the linear texture from the input images to generate adversarial examples. Benefiting from the above design concept, AdvSmo will generate adversarial examples with strong transferability and solid evasiveness. Finally, compared to the four advanced black-box adversarial attack methods, for the eight target models, the results show that AdvSmo improves the average attack success rate by 9% on the CIFAR-10 and 16% on the Tiny-ImageNet dataset compared to the best of these attack methods., Comment: 6 pages,3 figures

Published
2022

42. SSMI: How to Make Objects of Interest Disappear without Accessing Object Detectors?

Author

Xia, Hui, Zhang, Rui, Kang, Zi, and Jiang, Shuliang

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

Most black-box adversarial attack schemes for object detectors mainly face two shortcomings: requiring access to the target model and generating inefficient adversarial examples (failing to make objects disappear in large numbers). To overcome these shortcomings, we propose a black-box adversarial attack scheme based on semantic segmentation and model inversion (SSMI). We first locate the position of the target object using semantic segmentation techniques. Next, we design a neighborhood background pixel replacement to replace the target region pixels with background pixels to ensure that the pixel modifications are not easily detected by human vision. Finally, we reconstruct a machine-recognizable example and use the mask matrix to select pixels in the reconstructed example to modify the benign image to generate an adversarial example. Detailed experimental results show that SSMI can generate efficient adversarial examples to evade human-eye perception and make objects of interest disappear. And more importantly, SSMI outperforms existing same kinds of attacks. The maximum increase in new and disappearing labels is 16%, and the maximum decrease in mAP metrics for object detection is 36%., Comment: 6 pages, 2 figures

Published
2022

43. Revealing proton-coupled exchange mechanism in aqueous ion-exchange synthesis of nickel-rich layered cathodes for lithium-ion batteries

Author

Yu-Hong Luo, Qing-Lin Pan, Han-Xin Wei, Ying-De Huang, Pei-Yao Li, Lin-Bo Tang, Zhen-Yu Wang, Cheng Yan, Jing Mao, Ke-Hua Dai, Qing Wu, Xia-Hui Zhang, and Jun-Chao Zheng

Subjects
Ion exchange, Reaction mechanisms, Proton-coupled, Ni-rich oxides, Protonation, Lithiation, Mechanical engineering and machinery, TJ1-1570, Electronics, TK7800-8360
Abstract

Ion exchange is a promising synthetic method for alleviating severe cation mixing in traditional layered oxide materials for lithium-ion batteries, leading to enhanced structural stability. However, the underlying mechanisms of ion exchange are still not fully understood. Such a fundamental study of the ion-exchange mechanism is needed for achieving the controllable synthesis of layered oxides with a stable structure. Herein, we thoroughly unearth the underlying mechanism that triggers the ion exchange of Ni-rich materials in aqueous solutions by examining time-resolved structural evolution combined with theoretical calculations. Our results reveal that the reaction pathway of ion exchange can be divided into two steps: protonation and lithiation. The proton is the key to achieving charge balance in the ion exchange process, as revealed by X-ray adsorption spectroscopy and inductive coupled plasma analysis. In addition, the intermediate product shows high lattice distortion during ion exchange, but it ends up with a most stable product with high lattice energy. Such apparent discrepancies in lattice energy between materials before and after ion exchange emphasize the importance of synthetic design in structural stability. This work provides new insights into the ion-exchange synthesis of Ni-rich oxide materials, which advances the development of cathode materials for high-performance lithium-ion batteries.

Published
2024
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44. Suppressed Electrolyte Decomposition Behavior to Improve Cycling Performance of LiCoO2 under 4.6 V through the Regulation of Interfacial Adsorption Forces

Author

Chao Sun, Bing Zhao, Zhuan‐fang Jing, Hao Zhang, Qing Wen, He‐zhang Chen, Xia‐hui Zhang, and Jun‐chao Zheng

Subjects
cathode, electrolyte decomposition, interface adsorption, LiCoO2, lithium‐ion battery, Science
Abstract

Abstract Alleviating the decomposition of the electrolyte is of great significance to improving the cycle stability of cathodes, especially for LiCoO2 (LCO), its volumetric energy density can be effectively promoted by increasing the charge cutoff voltage to 4.6 V, thereby supporting the large‐scale application of clean energy. However, the rapid decomposition of the electrolyte under 4.6 V conditions not only loses the transport carrier for lithium ion, but also produces HF and insulators that destroy the interface of LCO and increase impedance. In this work, the decomposition of electrolyte is effectively suppressed by changing the adsorption force between LCO interface and EC. Density functional theory illustrates the LCO coated with lower electronegativity elements has a weaker adsorption force with the electrolyte, the adsorption energy between LCO@Mg and EC (0.49 eV) is weaker than that of LCO@Ti (0.73 eV). Meanwhile, based on the results of time of flight secondary ion mass spectrometry, conductivity‐atomic force microscopy, in situ differential electrochemical mass spectrometry, soft X‐ray absorption spectroscopy, and nuclear magnetic resonance, as the adsorption force increases, the electrolyte decomposes more seriously. This work provides a new perspective on the interaction between electrolyte and the interface of cathode and further improves the understanding of electrolyte decomposition.

Published
2024
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46. Probability distributions for kinetic roughening in the Kardar-Parisi-Zhang growth with long-range temporal and spatial correlations

Author

Chang, Zhichao and Xia, Hui

Subjects
Condensed Matter - Statistical Mechanics
Abstract

We investigate numerically the effects of long-range temporal and spatial correlations based on probability distribution of interface width $W(L,t)$ within the early growth regimes in the (1+1)-dimensional Kardar-Parisi-Zhang (KPZ) growth system. Through extensive numerical simulations, we find that long-range temporally correlated noise could not significantly impact the distribution form of interface width. Generally, $W(L,t)$ obeys Tracy-Widom Gaussian symplectic ensembles(TW-GSE) when the temporal correlation exponent $\theta \ge 0$. On the other hand, the effects of long-range spatially correlated noise are evidently different from the temporally correlated case. Our results show that, when the spatial correlation exponent $\rho \le 0.20$, the distribution form of $W(L,t)$ approaches to TW-GSE, and when $\rho > 0.20$, the distribution becomes more asymmetric, leptokurtic, and fat-tailed, and tends to an unknown form, which is similar to Gumbel distribution.

Published
2022

47. Pinning-depinning transitions in two classes of discrete elastic-string models in (2+1)-dimensions

Author

Wu, Yongxin and Xia, Hui

Subjects
Condensed Matter - Statistical Mechanics
Abstract

The pinning-depinning phase transitions of interfaces for two classes of discrete elastic-string models are inverstigated numerically. In the (1+1)-dimensions, we revisit these two elastic-string models with slight modification on growth rule, and compare with the previous numerical results. In the (2+1)-dimensional case, we perform extensive simulations on pinning-depinning transitions in these quenched models. For full comparisons in the physically relevant spatial dimensions, we also visit numerically two distinct quenched universality classes, including the quenched Edwards-Wilkinson (QEW) and the quenched Kardar-Parisi-Zhang (QKPZ) equations with and without external driving forces. The critical exponents of these quenched systems are numerically estimated. Our results show that the critical exponents satisfy scaling relations well, and these two discrete elastic-string models do not fall into the existing universality classes. In order to visually comparisons of these quenched systems in (2+1)-dimensional cases, we also exhibit surface morphologies with various external driving forces during the saturated time regimes.

Published
2022

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